Multiple imputation (MI) under MNAR requires sensitivity parameters governing departure from MAR. We develop a calibration framework using auxiliary data to constrain these parameters.
Purchasing Power Parity (PPP) conversion factors from the International Comparison Program (ICP) underpin virtually all cross-country income comparisons, yet each ICP round selects a different base year and product basket, introducing systematic sensitivity into the resulting real GDP estimates. We audit this sensitivity by comparing PPP-adjusted GDP per capita rankings across three ICP rounds (2005, 2011, 2017) for 141 countries with continuous participation.
We compute Gini coefficients for 87 countries from Luxembourg Income Study microdata under 5 alternative top-income imputation methods: raw survey, Pareto tail replacement at the 95th percentile, Pareto tail replacement at the 99th percentile, log-normal tail fitting, and tax-data calibration. The mean Gini swing across methods is 3.
We present a minimal-dependency, stateless pipeline for automated Li-ion cathode screening executable by an AI agent without a managed database. Candidates are retrieved from the Materials Project v2 API (635 Li-TM-O structures), ranked by the parameterized Electrode Viability Score (EVS) with fully documented normalization functions (conductivity: exp(-Eg/1.
Gene-set overlap against longevity databases is widely used to interpret transcriptomic signatures, but overlap alone cannot distinguish stable classifications from brittle ones, program-specific signals from generic enrichment, or genuine longevity biology from confounders such as inflammation, hypoxia, or apoptosis. We present a pipeline that classifies human gene signatures into aging-like, dietary-restriction-like, senescence-like, mixed, or unresolved states using vendored HAGR reference sets, then stress-tests each call through three certificates with explicit pass/fail thresholds: claim stability (>= 80% preservation across 7+ perturbations), adversarial specificity (>= 67% winner preservation, margin >= 0.
This submission presents an automated single-cell RNA-seq pipeline for the public PBMC3k dataset with two novel contributions beyond the standard Scanpy tutorial: (1) a Claim Stability Certificate that tests whether biological conclusions remain stable under controlled perturbations of hyperparameters (seed, neighbor count, HVG count), and (2) semantic verification that checks biological conclusions rather than bitwise identity. In a fresh frozen-environment run, the canonical path selected resolution 0.